Amazon CloudFront
by Amazon Web Services
CloudFront's configuration lives in its APIs: distributions with their origins and behaviors, cache policies, CloudFront Functions, origin access controls and the invalidations a team issues. That configuration explains changes in cache behavior and cost. Kept in the Lake beside AWS billing, it shows which distribution settings changed before a jump in data transfer charges.
- Category
- Cloud & Data Platforms
- Type
- CDN & edge
- Interface
- REST API
- Built with
- Connect Anything
- Credentials
- AWS access keys
02Data
What you can sync.
- Distributions
- Invalidations
- Cache policies
- Functions
- Origin access controls
Load Amazon CloudFront distributions into your Lake and model it in the Warehouse with the rest of your stack.
Need more? Name any other Amazon CloudFront data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- AWS access keys
Amazon CloudFront uses AWS access keys. You add the credentials once, when the AI asks for them, and it tells you where to create them in Amazon Web Services if you need help.
04Questions
Questions you can answer.
Once Amazon CloudFront data is in your Lake, ask an AI Mind in plain words or build the answer in DataPrism BI.
- Which distributions had cache policy changes in the week data transfer costs rose?
- How many invalidation paths did each team submit last month, and against which distributions?
- Which distributions still serve S3 origins without an origin access control?
- Which CloudFront Functions are attached to production behaviors, and when were they last updated?
05How it works
How it works in DataMind.
-
Pick Amazon CloudFront.
Open Lake, pick Amazon CloudFront in the source picker and name the connection. Connect Anything opens with a ready prompt that points the AI at the Amazon CloudFront API docs.
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Answer a few questions.
The AI reads the Amazon CloudFront documentation, then asks which credentials you will use, which data to sync (for example distributions and invalidations), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
The connector agent writes a Python connector for Amazon CloudFront, tests it against the live API and shows you sample rows. Then the data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
06Pairs
Works well with Amazon CloudFront.
Sources teams join with Amazon CloudFront in the Warehouse, each one connected the same way.
